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On Sat, 9 Aug 2014, Ulrich Drepper wrote:
If you are going to specialize for dim 2, I imagine you won't be computing normal distributions, you will only generate a point uniformy in a square and reject it if it is not in the ball? (interestingly enough this is used as a subroutine by the implementation of normal_distribution)We need to be *on* the circle, not inside.
Yes, you still need the normalization step (divide by the norm). It works whether you start from a uniform distribution in the disk or from a Gaussian in the plane, but the first one is easier to generate (generate points in a square until you get one in the disk). When the dimension becomes higher, the probability that a point in the cube actually belongs to the ball decreases, and it becomes cheaper to use a Gaussian.
-- Marc Glisse
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